A measure of explained risk in the proportional hazards model

被引：58
作者：
Heller, Glenn [1 ]
机构：
[1] Mem Sloan Kettering Canc Ctr, Dept Epidemiol & Biostat, New York, NY 10065 USA
来源：
BIOSTATISTICS | 2012年 / 13卷 / 02期
关键词：
Censored data; Entropy; Explained risk; Proportional hazards; Relative risk; SURVIVAL-DATA; PROSTATE-CANCER; DEPENDENCE; PREDICTION; RESIDUALS;
D O I：
10.1093/biostatistics/kxr047
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A measure of explained risk is developed for application with the proportional hazards model. The statistic, which is called the estimated explained relative risk, has a simple analytical form and is unaffected by censoring that is independent of survival time conditional on the covariates. An asymptotic confidence interval for the limiting value of the estimated explained relative risk is derived, and the role of individual factors in the computation of its estimate is established. Simulations are performed to compare the results of the estimated explained relative risk to other known explained risk measures with censored data. Prostate cancer data are used to demonstrate an analysis incorporating the proposed approach.
引用
收藏
页码：315 / 325
页数：11
相关论文
共 18 条
[1]   A contemporary prognostic nomogram for men with hormone-refractory metastatic prostate cancer: A TAX327 study analysis [J].
Armstrong, Andrew J. ;
Garrett-Mayer, Elizabeth S. ;
Yang, Yi-Chun Ou ;
de Wit, Ronald ;
Tannock, Ian F. ;
Eisenberger, Mario .
CLINICAL CANCER RESEARCH, 2007, 13 (21) :6396-6403
[2]  
Arnold V.I., 1989, MATH MODELS CLASSICA
[3]  
Graf E, 1999, STAT MED, V18, P2529
[4]  
GRAMBSCH PM, 1994, BIOMETRIKA, V81, P515
[5]   REGRESSION MODELING STRATEGIES FOR IMPROVED PROGNOSTIC PREDICTION [J].
HARRELL, FE ;
LEE, KL ;
CALIFF, RM ;
PRYOR, DB ;
ROSATI, RA .
STATISTICS IN MEDICINE, 1984, 3 (02) :143-152
[6]   Using SAS to calculate the Kent and O'Quigley measure of dependence for Cox proportional hazards regression model [J].
Heinzl, H .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2000, 63 (01) :71-76
[7]   PROBLEMS AND PREDICTION IN SURVIVAL-DATA ANALYSIS [J].
HENDERSON, R .
STATISTICS IN MEDICINE, 1995, 14 (02) :161-184
[8]   MEASURES OF DEPENDENCE FOR CENSORED SURVIVAL-DATA [J].
KENT, JT ;
OQUIGLEY, J .
BIOMETRIKA, 1988, 75 (03) :525-534
[9]  
KENT JT, 1983, BIOMETRIKA, V70, P163, DOI 10.1093/biomet/70.1.163
[10]   MEASURES OF EXPLAINED VARIATION FOR SURVIVAL-DATA [J].
KORN, EL ;
SIMON, R .
STATISTICS IN MEDICINE, 1990, 9 (05) :487-503
12